Model Predictive Controller Monitoring Based on Pattern Classification and PCA

Abstract

A pattern classification-based methodology is presented as a practical tool for monitoring Model Predictive Control (MPC) systems. Principal component analysis (PCA) is used, especially PCA and distance similarity factors, to classify a window of current, MPC operating data into one of several classes. Pattern classifiers are developed using a comprehensive… (More)

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